In this project the PI will design a comprehensive network-based framework that will allow the study of the attractors corresponding to signal transduction networks, and biological networks in general, even in the absence of quantitative information. A set of parsimonious methodologies will be developed that iteratively bridge qualitative and quantitative modeling, specifically graph theoretical analysis as well as Boolean, Boolean-continuous hybrid, and Hill-type continuous dynamic modeling methods. The proposed models allow for a direct interpretation of their results as they represent behaviors such as apoptosis, proliferation, migration, pathogen clearance, as output nodes of the network. The main hypothesis of this work is that the damage due to the cascading effects of a perturbation can be mitigated even if the original perturbation can no longer be reversed. The framework will be used to determine how node perturbations (changes in state or in interactions) change the output nodes dynamic attractors and furthermore to identify those interventions - such as externally supplying or depleting a node, or placing a node under the control of an upstream element - that can restore the normal dynamics of output nodes even in the presence of node perturbations.
Two specific aims will be pursued: (i) to develop a suite of network modeling methods to identify, filter and rank candidate restorative interventions, and (ii) to make these network modeling methods easily usable by a large community. All analysis methods will be implemented in the open-source library BooleanNet, which will feature a web-based interface, a network analysis layer and a visualization layer. The damage mitigation methodologies developed in this project have implications in addressing major societal needs such as sustainable food production, ecosystem restoration, and human health. This project will provide funding and cross-disciplinary training for a graduate student and a postdoctoral scholar, both co-advised by the PI and co-PI. Both investigators have extensive experience in co-advising and in mentoring of female and minority scientists at all levels. The project will provide research opportunities for Penn State undergraduates recruited by various means such as the Physics REU program and the Women in Science and Engineering program. This research will be incorporated into the courses taught by the PIs, including the undergraduate course Systems Biology and Networks and the graduate course Practical Data Analysis for Life Scientists, both attended by students from diverse departments. Groups of under-represented middle school students will be hosted during summer visits to Penn State as part of the Higher Achievement Program, a non-profit, academic support program that prepares students to complete high school and be college-ready. In addition, one member of the team will yearly attend the SACNAS (Society for the Advancement of Chicano and Native American Scientists) conference and participate in conversations with scientists and other activities designed to facilitate entry of minorities into careers in science.
This project is being jointly supported by the Physics of Living Systems program in the Division of Physics and the Physiological and Networks and Regulation Program in the Division of Molecular and Cellular Biosciences.
